We consider measurements from possibly zero-mean stochastic processes in a nonlinear filtering framework. This is a challenging problem, since it is only the second order properties of the measurements that bear information about the unknown state vector. The covariance function of the measurements can have both spatial and temporal correlation that depend on the state. Recently, a solution to this problem was presented for the case of Gaussian processes. We here extend the theory to Student's t processes. We illustrate the state observability by a simple but still realistic simulation example.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Non-linear filtering based on observations from Student's t processes


    Contributors:
    Saha, S. (author) / Orguner, U. (author) / Gustafsson, F. (author)


    Publication date :

    2012-03-01


    Size :

    721044 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Non-linear filtering based on observations from Gaussian processes

    Gustafsson, F / Saha, S / Orguner, U | IEEE | 2011


    Upgrading from Gaussian Processes to Student’s-T Processes

    Tracey, Brendan D. / Wolpert, David | AIAA | 2018


    Upgrading from Gaussian Processes to Student's-T Processes (AIAA 2018-1659)

    Tracey, Brendan D. / Wolpert, David | British Library Conference Proceedings | 2018


    High Integrity Localization of Intelligent Vehicles with Student's t Filtering and Fault Exclusion

    Al Hage, Joelle / Salvatico, Nicolo / Bonnifait, Philippe | IEEE | 2023


    Robust student’s t based nonlinear filter and smoother

    Yulong Huang / Yonggang Zhang / Ning Li et al. | IEEE | 2016